Industrial SO2 Emissions Research Articles

Get the real boss in position: Examining the environmental effect of ‘shared environmental accountability’ in China

China implemented the Shared Environmental Accountability between Party Secretaries and Government Officials (SEA) policy in August 2015, aiming to enhance environmental enforcement by holding both the secretaries of the Communist Party of China (Party secretaries) and government officials accountable for environmental issues. This paper examines the environmental effect of the SEA policy, with a particular focus on the role of bureaucrats' personal traits. Based on city-level data from 2011 to 2021, we find that the SEA policy leads to a differential reduction in industrial SO2 emissions and energy consumption by approximately 15.9 % and 32.0 % in cities that have a higher pressure of environmental protection. We also find that the pro-environmental effect of the SEA policy is mainly realized by enhancing energy efficiency and cleaner production. More importantly, we find that the environmental effect of the SEA policy is strengthened by hometown ties if Party secretaries have promotion prospects. Further improvements in emission reduction and energy saving could be achieved if certain countermeasures were undertaken so that Party secretaries, regardless of their promotion potential, are incentivized to faithfully implement environmental regulations.

Bayesian Network Analysis: Assessing and Restoring Ecological Vulnerability in the Shaanxi Section of the Qinling-Daba Mountains Under Global Warming Influences

Human activities, especially industrial production and urbanization, have significantly affected vegetation cover, water resource cycles, climate change, and biodiversity in the Qinling-Daba Mountain region and its surrounding areas. These activities contribute to complex and lasting impacts on ecological vulnerability. The Qinling Mountain region exhibits a complex interaction with human activities. The current research on the ecological vulnerability of the Qinling Mountain region primarily focuses on spatial distribution and the driving factors. This study innovatively applies the VSD assessment and Bayesian networks to systematically evaluate and simulate the ecological vulnerability of the study area over the past 20 years, which indicates that the integration of the VSD model with the Bayesian network model enables the simulation of dynamic relationships and interactions among various factors within the study areas, providing a more accurate assessment and prediction of ecosystem responses to diverse changes from a dynamic perspective. The key findings are as follows. (1) Areas of potential and slight vulnerability are concentrated in the Qinling-Daba mountainous regions. Over the past 20 years, areas of extreme and high vulnerability have significantly decreased, while areas of potential vulnerability and slight vulnerability have increased. (2) The key factors impacting ecological vulnerability during this period included industrial water use, SO2 emissions, industrial wastewater, and ecological water use. (3) Areas primarily hindering the transition to potential vulnerability are concentrated in well-developed small urban regions within basins. Furthermore, natural factors like altitude and temperature, which cannot be artificially regulated, are the major impediments to future ecological restoration. Therefore, this paper recommends natural restoration strategies based on environmental protection and governance strategies that prioritize green development as complementary measures. The discoveries of the paper provide a novel analytical method for the study of ecological vulnerability in mountainous areas, offering valuable insights for enhancing the accuracy of ecological risk prediction, fostering the integration of interdisciplinary research, and optimizing environmental governance and protection strategies.

The Impact of Carbon Emissions Trading Policy on Regional Economy and Pollution Reductions in Chinese Provinces

Carbon emissions trading policy is an important tool to achieve carbon peaking and carbon neutrality goals. In order to explore the effectiveness of carbon emissions trading policy, this paper adopts the difference-in-differences model to analyze the effects of China’s pilot policy on regional economic development and pollution reductions. The results show that carbon trading policy can significantly promote economic development and reduce total carbon emissions, industrial SO2 emissions and solid wastes production of pilot regions. Further research finds that there is significant regional difference in policy effectiveness, with the policy more effective in western areas. In addition to direct effects, carbon trading policy could exert an indirect effect on carbon emissions, air quality, industrial solid wastes and regional economic development by optimizing energy consumption structures and industrial structures and increasing technological investment. This result verifies the “Porter hypothesis”. China should improve the construction of national carbon trading markets, covering more industries, considering the regional differences and negative spillover effect.

The benefits and burdens of wind power systems in reaching China's renewable energy goals: Implications from resource and environment assessment

Recognizing the economy's growing reliance on global energy landscape transformation on wind power deployment, as well as the general reality that renewable facilities require lower operational but higher up-front inputs than fossil-based power systems, this paper focuses on the life-cycle burdens of wind power systems and their substitution benefits compared with coal-fired power systems. The estimation considers the consumption of nonrenewable sources of energy, emissions of greenhouse gases, and other environmental resource factors that have received significantly less research attention, such as industrial land use, water use, PM2.5, SO2, NOX, and Hg emissions. The scope of this study differs from earlier ones in that it includes a comprehensive description of all the equipment, materials, and services used, as opposed to earlier studies that either omit crucial supporting infrastructure or just focus on the plant's physical structure as its primary materials. Results based on a typical plant in China show that the state-of-the-art onshore wind power systems can provide significant reductions in nonrenewable energy use (9.2 MJ/kWh) and GHG emissions (782.8 GtCO2/kWh). To produce an equivalent amount of electricity, wind power systems require more than three times industrial land use and almost one-third of industrial water use of that for traditional coal-fired power systems. The avoided SO2, Hg, PM2.5, and NOX emissions per unit of electricity generation account for 60.6%–89.3% of the total air pollution emissions induced by supercritical coal-fired power systems. By integrating 3797 operating plant-specific data and fixed-point wind energy information, this study scales up results of the single plant to a country level. The macro picture implies different opportunities born by wind power systems in easing multiple resource and environmental pressures, highlighting the significance of designing hierarchical strategies to improve penetration levels of wind power. By 2050, cumulative climate benefits obtained from onshore wind power technology are predicted to reach 74.2 Gt CO2, achieving around 17.2%–45.5% of the national carbon-neutral goal.

Research on the impact of manufacturing servitization on environmental pollution: spatial econometric analysis of sulfur dioxide based on 284 prefecture-level cities

Using China’s regional input–output table, the paper constructs indicators of manufacturing servitization, matches manufacturing servitization at the regional level with city data, and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide (SO2) emissions within the classical Environmental Kuznets Curve (EKC) framework. The results show that manufacturing servitization can reduce SO2 emissions. Producer servitization and consumptive services can both significantly reduce industrial SO2 emissions. Transportation and warehousing servitization, information servitization, leasing, and commercial servitization, technology research and development servitization significantly reduce SO2emissions; technology research and development servitization, in particular, have the largest influence coefficient, while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant. The study also found that servitization reduced the SO2 emissions through technological innovation and industrial structure upgrading.

How to effectively achieve air pollutant reduction and carbon mitigation in China's industrial sector? A study based on decomposition analysis and scenario simulation.

Reducing air pollutant and carbon emissions in the industrial sector is crucial for the ecological civilization construction in China. In this study, we first employ the generalized Divisia index method to analyze the driving factors of industrial CO2 and SO2 emissions, incorporating fixed asset investment and R&D input. The key sub-sectors that exert significant impact on emissions of the whole industrial sector are identified. And then, scenario analysis and Monte Carlo simulation are utilized to predict future trends and potential for reducing CO2 and SO2 emissions. Furthermore, the carbon peaking time of the industrial sub-sectors is investigated. The results indicate that fixed asset investment and R&D input both have played positive roles in CO2 and SO2 emissions. Emission reduction is mainly driven by investment emission intensity, output emission intensity, and R&D emission intensity. Sub-sectors S09, S10, S11, S12, and S18 present substantial potential for reducing air pollutant and carbon emissions. Although SO2 emissions from the industrial sector are projected to decrease in the future, the peak of CO2 emissions have not been reached. The carbon peak time for the whole industrial sector is predicted in 2025, with the peak of 7892.33 Mt. The five key sub-sectors are anticipated to reach the respective carbon emission peaks at different times. Therefore, to effectively implement industrial air pollutant and carbon reduction, the role of fixed asset investment and R&D input should be fully utilized, and high-energy consumption and high-emission sub-sectors should be prioritized for action.

Spatial difference-in-differences analysis of smart city pilot policy and industrial pollution reduction: the mediating role of S&T fiscal expenditure.

Smart city has become one of the most important tool to achieve digital transformation and intelligent development. However, the impacts of smart city pilots (SCP) on different industrial pollution have yet to be tested, and the mechanisms of SCP affect industrial pollution could be richer. In this paper, we construct a spatial difference-in-difference model for 2004-2019 by mapping SCP policy to Chinese city data to systematically quantify the impact and its potential mechanisms of digital transformation on industrial pollution. Our results show that the SCP policy achieves industrial pollution reduction targets, on average, wastewater and SO2 emissions decreased by 6.4% and 6.5%, respectively. Cities with SCP policy have more industrial pollution compared to cities without SCP policy, implying a beggar-thy-neighbor effect of SCP policy. Furthermore, significant regional disparities come to light; SCP policy in the Pearl River Delta exceeds other regions such as the Yangtze River Delta and Jing-Jin-Ji city cluster in terms of realizing the impact of industrial pollution reduction. Importantly, mechanism analysis indicated that the SCP reduced industrial pollution was partially mediated by government S&T fiscal expenditure.

Impact of industrial robots on environmental pollution: evidence from China

The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO2, and industrial dust, the impacts generated by industrial robots are exhibiting trends of a “W” shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution.

Decomposition of industrial SO2 emission in China with firm entry and exit

The difficulty of the sulfur dioxide (SO2) pollution control task has deepened step by step in recent years, while the marginal cost of environmental protection in China has also been higher. Therefore, it is necessary to study the main impact factors of China's industrial SO2 pollution. Based on China's Industrial Environmental Statistics Database from 2004 to 2013, this paper extends the Index Decomposition Analysis (IDA) with firm entry and exit to conduct a micro-level decomposition study. The industrial SO2 emission in China is decomposed into scale effect, composition effect, firm growth effect, and firm selection effect. Also, we use the Dagum Gini coefficient to analyze the spatial differences of firm growth effect and selection effect between the eastern, central, and western regions in China. This paper finds that the main contribution of industrial SO2 emission control in China is the firm growth effect, which was −103% between 2004 and 2013. And the second largest contribution term is the firm selection effect, which is −18%, while the composition effect is −15%. In terms of temporal patterns, the size of the firm growth effect shrinks as time grows, and the composition effect changes from negative to positive after 2009. For spatial difference analysis, the Dagum Gini coefficient of technique effect and firm growth effect between different regions have become smaller and smaller over time, while the spatial differences of firm selection effect between regions remain unchanged.

Does the environmental protection tax reduce environmental pollution? Evidence from a quasi-natural experiment in China.

The environmental protection tax (EPT) is an important environmental policy in China. However, it remains unclear whether the EPT has reduced environmental pollution effectively since its implementation in 2018. Based on the panel data of 229 prefecture-level cities in China during 2015-2019 and the difference-in-differences (DID) model, this study empirically assesses the causal effect of the EPT on environmental pollution. It is found that the EPT has a significantly negative effect on industrial sulfur dioxide (SO2) and industrial soot (dust) emissions but has no significant impact on industrial wastewater emissions. The mechanism analysis reveals that the EPT has the tax enforcement effect and energy efficiency effect, that is, the EPT reduces pollution emissions through increasing actual tax burden and improving the efficiency of energy utilization. However, the innovation effect is weak, which is only effective in reducing industrial SO2 emissions. Finally, we compare how different types of cities responded to the EPT. The results show that the EPT has limited effect on environmental pollution in large cities and southern China.

Can Environmental Centralization Enhance Emission Reductions?—Evidence from China’s Vertical Management Reform

In the industrialization process, the difficulty in implementing environmental protection and enhancing the effect of environmental emission reduction are common problems to the developing countries, which are directly related to the quality of social development. This paper takes environmental centralization as the solution idea, takes the vertical management reform of environmental protection agencies implemented in China as the research object, and evaluates the environmental emission reduction effect and mechanism of action of centralized reform based on provincial environmental economic panel data using difference-in-differences model and intermediary model. The following conclusions are drawn: (1) The environmental centralization has significantly improved the provincial environmental emission reduction effect. After China’s vertical management reforms were implemented, per capita CO2 emissions decreased by 11.1%, and industrial source SO2 emissions fell by 35.7%. (2) By increasing investment in urban environmental infrastructure construction, the reform has raised the level of investment and regulation in environmental protection construction, which in turn has effectively improved the ability to reduce environmental emissions. (3) After the implementation of the reform, the emission reduction effects of the reform on per capita CO2 and industrial source SO2 are 10.1% and 14.2% higher in provinces with lower industrial output value compared to those with higher industrial output value. At the same time, the effect of reform in provinces with a strong degree of local government intervention was significantly lower than that in provinces with a weak degree of local government intervention. The emission reduction effects of the reform implementation are 10.2% (per capita CO2) and 30.5% (industrial source SO2) lower, respectively. Based on the above findings, this paper argues that environmental centralization is an effective measure to advance the improvement of environmental quality and efficiency. In addition, China’s reform experience has implications for other developing countries.

A Study on the Effect of Innovation-Driven Policies on Industrial Pollution Reduction: Evidence from 276 Cities in China

The societal effects of industrial pollution have spurred heated debates, but more research into the influence and internal mechanism of innovative pilot city policies (IPCPs) on industrial emissions is needed. Using panel data from 276 Chinese cities between 2004 and 2018, the study employs a multi-period difference-in-differences model to explore the effects and mechanisms of pilot policies on industrial SO2 emissions, with a specific focus on how they can be mitigated by innovative techniques. The results indicate that (1) the Chinese innovative pilot city policies (CIPCPs) significantly reduced emissions in urban areas; (2) the concentration of talent, innovation policy, venture capital, and technology plays a pivotal role; and (3) the SO2 reduction effects are more pronounced in larger cities, such as super-large, mega-, and first-tier cities in the southeast, and in cities with a high market potential. This study provides empirical evidence to support the promotion of sustainable economic and social development, the resolution of environmental pollution problems, and the enhancement of public health.

Unraveling spatiotemporal patterns and multiple driving factors of surface ozone across China and its urban agglomerations management strategies

Since State Council launched the Action Plan for Air Pollution Prevention and Control in 2013, national concentration of fine particulate matter (PM2.5) has continued to decline in China, while surface ozone (O3) pollution shows an obvious rise. To identity hot regions and develop targeted policy, the spatiotemporal O3 variation and its population-weighted exposure features were analyzed in 337 cities across China, using autocorrelation analysis and grid exposure calculation. In the identified hot urban agglomerations, the correlation analysis and geographic weighted regression model (GWR) were used to study related meteorological factors and socioeconomic driving factors. O3 pollution and its human exposure were found to have significant spatial aggregation characteristics, showing a need for regional management policy. Beijing-Tianjin-Hebei Urban Agglomeration (BTH-UA), Central Plains Urban Agglomeration (CP-UA), and Yangtze River Delta Urban Agglomeration (YRD-UA) were identified as hot regions where O3 concentration exceeded 160 μg·m−3, exceedance rate was over 20% and population-weighted exposure risk was relatively high. Correlation analysis in the hot regions indicated high surface temperature, low relative humidity, and low wind speed were positive to O3 increase. Further, GWR results revealed that O3 in the majority of cities was positively related with population density (PD), the per capita GDP (Per_GDP), industrial soot emissions (ISE), industrial SO2 emissions (ISO2), and average annual concentration of inhaled fine particulate matter (PM10), and negatively related with total land area of administrative region (Administration) and area of green land (Green). From the regional driving factor difference, the targeted UA management policy was provided.

The path towards sustainable finance: Venture capital and air pollution in China

Financing sustainable growth has attracted global attention and discussion in recent years. This study investigates the effect of venture capital, as a potential source of sustainable finance, on air pollution in China from 2003 to 2016. Using the unique Government Guidance Fund as instrumental variable, we find that venture capital activities have significantly reduced local air pollution in cities of China. To be specific, a one standard deviation increase in the VC amount leads to 4% decrease in PM2.5 concentration and 6% reduction in industrial SO2 emission. The effects are insensitive to a wide range of robustness tests. Cities characterized by more rigorous environmental supervision, superior business environments, and stronger innovation incentives benefit more from venture capital activities. We further show that venture capital helps improve local air quality by boosting general and green innovation, increasing the investment of new green enterprises, as well as crowding out the investment of polluting industries.

The spatial spillover effect of higher SO2 emission tax rates on PM2.5 concentration in China

In this paper, the adoption of SO2 emission tax rates higher than the legal minimum standard is regarded as a noteworthy policy reform in China (quasi-natural experiment), and a spatial Difference-in-Differences (Spatial-DID) model is constructed to test the direct effects (local effects) and indirect effects (spatial spillover effects) of SO2 emission tax policy reform on PM2.5 concentrations in the atmosphere of 285 China’s cities. The estimation and calculation results of the Spatial-DID model show that the SO2 emission tax policy reform can significantly reduce local PM2.5 concentration and significantly promote PM2.5 concentration in surrounding areas. The results of heterogeneity analysis show that the SO2 emission tax policy reform can produce a relatively more beneficial spatial spillover effect in eastern cities and higher administrative level cities, while the pollutants emission rights trading and the reform of NOx emission tax rates can produce beneficial spatial spillover effects when cooperating with the reform of SO2 emission tax rates. The results of the mediation effect analysis show that the higher SO2 emission tax rate can aggravate the surrounding PM2.5 pollution by promoting the aggregation level of industrial production factors and the industrial SO2 emission intensity in the surrounding areas, which can support the existence of the pollution heaven effect.

The health impacts of two policies regulating SO2 air pollution: Evidence from China

In developing countries widespread air pollution poses a major threat to public health calling for effective environmental regulation. This paper adds to the limited literature on the health impact of different environmental regulations. Using data from eight waves of the China Health and Nutrition Survey (1993–2015), we employ a difference-in-differences model to investigate the health impact of two policies combatting SO2 air pollution: the command-and-control environmental regulation represented by the Two Control Zones (TCZ) and the market-oriented environmental regulation represented by the SO2 Emissions Trading Scheme (ETS). The main findings are that the TCZ policy resulted in a 39% reduction in the 4-week prevalence of air pollution-related diseases through channels such as reducing industrial SO2 emissions and industrial fumes emissions, and increasing individuals' amounts of physical exercise. In contrast, the ETS had no positive health effects, likely due to imperfect market mechanisms and environmental policy uncertainties. The health impact of the TCZ was most pronounced for respiratory illnesses, and was increasing over the period during which the policy was implemented. The positive health impact is stronger for outdoor, less educated, and lower income workers. Residents in Eastern regions and urban areas (especially the rural hukou holders living there) benefitted more from the environmental regulation.

Evaluating the Causal Effects of Emissions Trading Policy on Emission Reductions Based on Nonlinear Difference-In-Difference Model

Based on panel data from 30 provinces, cities, and autonomous regions from 2001 to 2019, this paper uses the nonlinear difference-in-difference (DID) method to estimate the distribution of causal effects of emissions trading policy on emission reduction in Chinese industrial enterprises, and examines the heterogeneity of the effects. The empirical results show that (1) the emissions trading policy has a significant effect on industrial SO2 emissions reduction in China, where the reduction effect is larger in non-pilot areas than in pilot areas; (2) the policy effects are not proportional to the regional SO2 emissions intensity, and the emissions trading policy is not more effective in regions with higher industrial SO2 emissions intensities. One advantage of this paper is the use of nonlinear DID to estimate the emissions reduction effect, which eliminates the bias problem caused by the strict linearity assumption of the classical DID method. Another advantage is that the combination of the random forest method avoids the subjectivity in the selection of control variables and uses distribution effects for multilevel comparisons. This method improves the validity of estimating the effect of emissions trading policy and provides targeted policy suggestions for the effective promotion of system implementation, all of which have academic and application value.

The effect of environmental regulation on the marginal abatement cost of industrial firms: Evidence from the 11th Five-Year Plan in China

The Chinese government set specific provincial reduction targets for sulfur dioxide (SO2) and chemical oxygen demand (COD) in the 11th Five-Year Plan. However, due to the limitations of firm-level data, there is a research gap on the impact of this policy on the marginal abatement cost (shadow price) of targeted pollutants for industrial firms. First, we estimate the shadow prices of SO2 and COD emissions for industrial firms in China from 1998 to 2009 using the quadratic output directional distance function based on the stochastic frontier analysis (SFA). We also use the Environmental Survey and Reporting database, which is a unique nationwide firm-level database including firm-level emission information. Then, using the difference-in-difference-in-differences (DDD) strategy and combining the variation in pollution reduction targets across provinces with the before-and-after policy change, as well as the firms' emissions, we identify the effect of the provincial reduction targets on the shadow prices of the two pollutants. The estimated average shadow prices of SO2 and COD emissions are 3454.96 yuan/ton and 17,560.18 yuan/ton, respectively. The heterogeneous characteristics show that non-state-owned enterprises (non-SOEs), large-scale firms, and firms in the eastern region have higher shadow prices than state-owned enterprises (SOEs), small and medium-scale firms, and firms in the central and western regions. The DDD estimations show that the setting of provincial reduction targets significantly increases the shadow prices of SO2 and COD emissions for industrial firms. Specifically, when the pollution reduction target is one standard deviation higher than the mean, the shadow prices of industrial firms' SO2 and COD emissions increase by 26.11 yuan/ton and 85.52 yuan/ton, respectively, whose SO2 and COD emissions are 10% higher than the average value. Finally, several policy implications are hereby proposed.

Can raising trade barriers curb industrial pollution emissions?

The development of foreign trade and industrial pollution control is an important theme of government governance today. Based on the institutional background of rising international trade protectionism, this study examines the impact of trade barriers on industrial pollution emissions by using different measurement methods and data from 16 industrial sectors in 10 major countries. The results show that lowering trade barriers can significantly reduce industrial pollution emissions, considering the impact of potential endogenous problems. Heterogeneity analysis shows that reducing trade barriers in developed countries can reduce industrial SO2-emission intensity, while the opposite is true in developing countries. Trade barriers have the greatest effect on the pollution-emission intensity of technology-intensive industries, followed by labor-intensive and capital-intensive industries. Mechanism analysis shows that trade barriers affect industrial pollution-emission intensity through both pollution emission and industrial output and that energy-use intensity and biased technological progress are important mechanisms. This study provides a useful reference for governments to promote foreign trade development and ecological and environmental protection.

Impact of foreign direct investment on economy, environment, technology, productivity and energy of the countries

In today's world, attracting Foreign Direct Investment (FDI) is one of the essential tasks of governments. But what effect will the absorption of Foreign Direct Investment have on that society? Based on the review of 18 articles, the researcher has categorized these effects into the following 5 factors. These factors belong to Economy, Environment, Technology, Productivity, and Energy. Following the results of previous studies, the impacts of the five factors mentioned on communities in the effect of FDI are reviewed. The Boolean search methodology is chosen as the methodology, also the finding of the researcher is mentioned in the paragraphs below. FDI not only aids in the development of this industry, but it also has a substantial impact on the micro and macro levels. FDI has a favorable impact on the growth rate of per capita GDP. In addition, the African continent saw significant economic expansion. The impact of financial systems may explain why developing-country correlations are low while developed-country saving-investment correlations are strong. the impact of GDP and energy usage on Carbon dioxide emissions are significant, whereas the impact of FDI on Carbon dioxide emissions is positive but minor. Industrial SO2 emissions will increase by 0.098 percent for every 1% growth in FDI capital stock. FDI rising emissions in middle-income countries in the near term while reduces them in high-income nations. FDI from TMH areas has a substantial beneficial influence on the productivity of the wood products industry at the industrial level. On energy consumption, FDI revealed a negative scale impact, a structural effect, and a positive technical impact. In the end, the impact of foreign direct investment on worker productivity is positive. The researcher recommends that politicians make every effort to improve their country's political and judicial conditions to attract more FDI to their countries.